Suppr超能文献

舆情能量波动分析:基于社交网络事件的社会群体意见建模

The fluctuation analysis of public opinion energy: Modeling social group opinion base on the event of social networks.

作者信息

Shi Yayong, Qi Jianpeng, Wang Rui

机构信息

School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing 100083, China.

Shunde Graduate School of University of Science and Technology Beijing, Foshan 528300, China.

出版信息

Intell Syst Appl. 2022 May;14:200072. doi: 10.1016/j.iswa.2022.200072. Epub 2022 Mar 7.

Abstract

In the period of Corona Virus Disease 2019 (COVID-19), millions of people participate in the discussion of COVID-19 on the Internet, which can easily trigger public opinion and threaten social stability. To find out the relationship between the intergroup variability in numbers and perspectives and the dynamic change of the number of infected people, this paper defines the public focus level to quantify the level of attention of people to the information related to an epidemic situation, and the POF model based on the level of epidemic focus is proposed. In this paper, we have carried out simulation experiments in small-world networks and scale-free networks, respectively, to explore the relationship between the model parameters and the spreading range and speed of each population. Furthermore, the paper also analyzed all the original microblog posts published by the People's Daily from January 14, 2020, to February 12, 2020, and compared the data simulated by the POF model with the real data from the People's Daily, the simulation data and the real data can be well fitted to prove the reliability of the model.

摘要

在2019年冠状病毒病(COVID-19)期间,数以百万计的人在互联网上参与关于COVID-19的讨论,这很容易引发公众舆论并威胁社会稳定。为了找出群体间数量和观点的变异性与感染者数量动态变化之间的关系,本文定义了公众关注水平来量化人们对疫情相关信息的关注程度,并提出了基于疫情关注水平的POF模型。本文分别在小世界网络和无标度网络中进行了模拟实验,以探索模型参数与各群体传播范围和速度之间的关系。此外,本文还分析了《人民日报》在2020年1月14日至2020年2月12日期间发布的所有原创微博文章,并将POF模型模拟的数据与《人民日报》的真实数据进行了比较,模拟数据与真实数据能够很好地拟合,证明了该模型的可靠性。

相似文献

1
The fluctuation analysis of public opinion energy: Modeling social group opinion base on the event of social networks.
Intell Syst Appl. 2022 May;14:200072. doi: 10.1016/j.iswa.2022.200072. Epub 2022 Mar 7.
2
Multi-stage Internet public opinion risk grading analysis of public health emergencies: An empirical study on Microblog in COVID-19.
Inf Process Manag. 2022 Jan;59(1):102796. doi: 10.1016/j.ipm.2021.102796. Epub 2021 Oct 26.
3
Modeling and simulation of microblog-based public health emergency-associated public opinion communication.
Inf Process Manag. 2022 Mar;59(2):102846. doi: 10.1016/j.ipm.2021.102846. Epub 2021 Dec 16.
6
Public opinion communication mechanism of public health emergencies in Weibo: take the COVID-19 epidemic as an example.
Front Public Health. 2023 Nov 9;11:1276083. doi: 10.3389/fpubh.2023.1276083. eCollection 2023.
8
Modeling COVID-19 spread using multi-agent simulation with small-world network approach.
BMC Public Health. 2024 Mar 2;24(1):672. doi: 10.1186/s12889-024-18157-x.
10
Hot-topics cross-propagation and opinion-transfer dynamics in the Chinese Sina-microblog social media: A modeling study.
J Theor Biol. 2023 Jun 7;566:111480. doi: 10.1016/j.jtbi.2023.111480. Epub 2023 Mar 31.

本文引用的文献

1
Mathematical modeling for COVID-19 transmission dynamics: A case study in Ethiopia.
Results Phys. 2022 Mar;34:105191. doi: 10.1016/j.rinp.2022.105191. Epub 2022 Jan 15.
2
Spatial evolution patterns of public panic on Chinese social networks amidst the COVID-19 pandemic.
Int J Disaster Risk Reduct. 2022 Feb 15;70:102762. doi: 10.1016/j.ijdrr.2021.102762. Epub 2022 Jan 3.
3
Multi-stage Internet public opinion risk grading analysis of public health emergencies: An empirical study on Microblog in COVID-19.
Inf Process Manag. 2022 Jan;59(1):102796. doi: 10.1016/j.ipm.2021.102796. Epub 2021 Oct 26.
5
A geometric analysis of the SIRS epidemiological model on a homogeneous network.
J Math Biol. 2021 Sep 22;83(4):37. doi: 10.1007/s00285-021-01664-5.
6
An analysis of COVID-19 vaccine sentiments and opinions on Twitter.
Int J Infect Dis. 2021 Jul;108:256-262. doi: 10.1016/j.ijid.2021.05.059. Epub 2021 May 27.
7
Range of reproduction number estimates for COVID-19 spread.
Biochem Biophys Res Commun. 2021 Jan 29;538:253-258. doi: 10.1016/j.bbrc.2020.12.003. Epub 2020 Dec 9.
8
Social interaction layers in complex networks for the dynamical epidemic modeling of COVID-19 in Brazil.
Physica A. 2021 Feb 15;564:125498. doi: 10.1016/j.physa.2020.125498. Epub 2020 Nov 12.
10
Dynamics of the COVID-19 basic reproduction numbers in different countries.
Sci Bull (Beijing). 2021 Feb 15;66(3):229-232. doi: 10.1016/j.scib.2020.10.008. Epub 2020 Oct 15.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验